Re: Trends in the treatment of ductal carcinoma in situ of the breast.
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Breast Neoplasms↗
Biomedical subjects
Heather Taffet Gold
Publications and source records attributed to Heather Taffet Gold.
Variations in treatment for ductal carcinoma in situ in elderly women.
OBJECTIVE: The objective of this study is to quantify variation and variability in treatment of ductal carcinoma in situ (DCIS) over time and across registries of the Surveillance, Epidemiology, and End Results (SEER) program; to assess diffusion of treatments (breast-conserving surgery [BCS], BCS with radiotherapy, and mastectomy); and to identify correlates of treatment choice. DATA: The linked SEER-Medicare database from 1991 to 1996 includes 2701 women aged 65 and older diagnosed with unilateral DCIS. 1990 census data provide socioeconomic variables at the zip-code level, and the 1999 Dartmouth Atlas of Health Care provides number of radiation oncologists. STUDY DESIGN: Bivariate and multivariate analyses of retrospective cohort data assess factors that explain treatment choice. The multivariate model includes controls for comorbidity, marital status, age, race, education, poverty, rural, and radiation oncologists per 100,000 population. Chi-squared tests assess differences in treatment rates by registry and by year. Diffusion of treatments is analyzed by predicting yearly mean treatment rates and yearly variation in treatment rates across geographic areas and over time. RESULTS: There are significant geographic and temporal differences in treatment rates for DCIS with increasing use of BCS alone. Treatment choice is explained by SEER registry, diagnosis year, marital status, race, age, urban/rural status, educational attainment, and number of radiation oncologists. Variability in treatment of DCIS is increasing during the study period. CONCLUSIONS: Findings indicate that diagnosis year and socioeconomic factors explain treatment choice for DCIS, but unexplained variation at the geographic-region level remains. Increasing variability in treatment implies continued uncertainty about optimal treatment of DCIS.
Age Factors↗
How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions?
BACKGROUND: There is limited evidence about the extent to which sensitivity analysis has been used in the cost-effectiveness literature. Sensitivity analyses for health-related QOL (HR-QOL), cost and discount rate economic parameters are of particular interest because they measure the effects of methodological and estimation uncertainties. AIM: To investigate the use of sensitivity analyses in the pharmaceutical cost-utility literature in order to test whether a change in economic parameters could result in a different conclusion regarding the cost effectiveness of the intervention analysed. METHODS: Cost-utility analyses of pharmaceuticals identified in a prior comprehensive audit (70 articles) were reviewed and further audited. For each base case for which sensitivity analyses were reported (n = 122), up to two sensitivity analyses for HR-QOL (n = 133), cost (n = 99), and discount rate (n = 128) were examined. Article mentions of thresholds for acceptable cost-utility ratios were recorded (total 36). Cost-utility ratios were denominated in US dollars for the year reported in each of the original articles in order to determine whether a different conclusion would have been indicated at the time the article was published. Quality ratings from the original audit for articles where sensitivity analysis results crossed the cost-utility ratio threshold above the base-case result were compared with those that did not. RESULTS: The most frequently mentioned cost-utility thresholds were $US20,000/QALY, $US50,000/QALY, and $US100,000/QALY. The proportions of sensitivity analyses reporting quantitative results that crossed the threshold above the base-case results (or where the sensitivity analysis result was dominated) were 31% for HR-QOL sensitivity analyses, 20% for cost-sensitivity analyses, and 15% for discount-rate sensitivity analyses. Almost half of the discount-rate sensitivity analyses did not report quantitative results. Articles that reported sensitivity analyses where results crossed the cost-utility threshold above the base-case results (n = 25) were of somewhat higher quality, and were more likely to justify their sensitivity analysis parameters, than those that did not (n = 45), but the overall quality rating was only moderate. CONCLUSIONS: Sensitivity analyses for economic parameters are widely reported and often identify whether choosing different assumptions leads to a different conclusion regarding cost effectiveness. Changes in HR-QOL and cost parameters should be used to test alternative guideline recommendations when there is uncertainty regarding these parameters. Changes in discount rates less frequently produce results that would change the conclusion about cost effectiveness. Improving the overall quality of published studies and describing the justifications for parameter ranges would allow more meaningful conclusions to be drawn from sensitivity analyses.
Costs and Cost Analysis↗